IRT AND LC-IRT MODELS FOR ITEMS WITH ORDINAL POLYTOMOUS RESPONSES
نویسندگان
چکیده
منابع مشابه
Nonignorable data in IRT models: Polytomous responses and response propensity models with covariates
Missing data usually present special problems for statistical analyses, especially when the data are not missing at random, that is, when the ignorability principle defined by Rubin (1976) does not hold. Recently, a substantial number of articles have been published on model-based procedures to handle nonignorable missing data due to item nonresponse (Holman & Glas, 2005; Glas & Pimentel, 2008;...
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A structural multilevel model is presented where some of the variables cannot be observed directly but are measured using tests or questionnaires. Observed dichotomous or ordinal polytomous response data serve to measure the latent variables using an item response theory model. The latent variables can be defined at any level of the multilevel model. A Bayesian procedure Markov chain Monte Carl...
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A real-data simulation of computerized adaptive testing (CAT) is an important step in real-life CAT applications. Such a simulation allows CAT developers to evaluate important features of the CAT system, such as item selection and stopping rules, before live testing. SIMPOLYCAT, an SAS macro program, was created by the authors to conduct real-data CAT simulations based on polytomous item respon...
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Item response theory models are often applied when a number items are used to measure a unidimensional latent variable. Originally proposed within educational research, they are now also being used when focus is on e.g. physical functioning or psychological well-being. Modern applications often need more general models, typically models for multidimensional latent variables or longitudinal mode...
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ژورنال
عنوان ژورنال: Ekonometria
سال: 2017
ISSN: 1507-3866,2449-9994
DOI: 10.15611/ekt.2017.4.04